The present invention relates generally to database systems. More particularly, the invention is a computer-implemented method that allows data in different databases, which may have different formats and structures, to be shared without remodeling the data to fit an existing data convention. The system and method provide for transforming relational database information into a hierarchical data representation format.
Modern information resources often comprise huge databases that must be searched, in order to extract useful information. One example of this includes data found on global information networks. With the wealth of information available today, and its value to businesses, managing information effectively has become essential. However, existing database technologies, including recent advances in database integration, are often constrained when interacting with multiple, voluminous data sources.
As a growing number of companies establish Business-to-Business (B2B) and Business-to-Consumer (B2C) relationships using a global communications network, such as the Internet, traditional data sharing among multiple large data sources has become increasingly problematic. Data required by businesses is often stored in multiple databases, or supplied by third party companies. Additionally, data sharing difficulties are often magnified as companies attempt to integrate internal and external databases that are always increasing in number and kind. As a result, combining data from separate sources typically creates an expensive and time-consuming systems integration task.
In order to exchange data between entities, data standardization has been used in an attempt to achieve data integration and interoperability. Standards bodies like RosettaNet, BizTalk, OASIS, and ACORD, are available to standardize data so that it can be exchanged more easily. However, there are many problems presented by these solutions. In order to participate in a consortium, all participants' data has to be modeled in the same manner. Additionally, various consortia and standards bodies that have been established to handle similar types of data often have different standards that correspond to specific industries. Also, the adoption of standards is slow, because businesses within each industry still modify data to fit their own company requirements. Hence, given the number of different consortia, standards, and industries, there is still a need for a standard means to exchange data and data structure between different data structures and databases, among companies of the same and different industries, and even among departments of single companies.
One current approach to filling this need is to painstakingly map one field of data to another, in order to exchange the data with a “non-conformant” entity; that is, one that uses different data structure standards. This process must be repeated not only for every field but also for every different exchange. These solutions to the exchange problem are generally custom “hard-coded” solutions. An efficient, user-configurable method for sharing data between different data structures is still lacking.
Database technologies, such as Structured Query language (SQL), Open Database Connectivity (ODBC), Extensible Markup Language (XML), and other tools, have been developed to facilitate database integration. As beneficial as these technologies may be, however, they have failed to address inherent differences in the structure and organization of databases, in addition to the contents. These differences are important, because the richness of the original structure often contributes to the value of its underlying data.
For example, when attempting to store the same type of data or object, such as a customer description, database designers may use different field names, formats, and structures. Fields contained in one database may not be used in another. If understood and logically integrated, these disparities can provide valuable information, such as how a company gains competitive advantage based on its data structuring. Unfortunately, today's database technologies often cleanse the disparities out of data to make it conform to standards of form and structure. Examples include databases that are converted from one representation to another representation and expressed in XML, using its corresponding hierarchical structure.
Integrating data from multiple environments and formats into a single interoperable structure is particularly necessary to seamless B2B electronic commerce (e-Commerce), and XML enables data to look much more alike than any previous format. However, there are still problems with using XML to represent data. These problems fall into two major categories: 1.) dirty and naturally occurring data perplex XML searching and storage and 2.) data formats or data schemas in the original databases that offer competitive advantage or better reflect the true model of the business and its data, are sacrificed to standards consortia. This means that the database formats or schemas have to be fit into the consortia data standards, which requires a highly skilled technical staff to spend a large amount of time comparing one database schema to another. Moreover, the standards being used and developed to overcome these data exchange barriers sacrifice competitive advantage for interoperability. Today, businesses require both.
Conforming to industry standards may also raise other issues, such as intellectual property issues; the ability for data modeled to a specific consortium standard to communicate with other consortia that use a different model or standard; and the handling of legacy data in multiple formats.